What is feature embedding in the context of convolutional neural networks?
The term feature embedding appears to be a synonym for feature extraction, feature learning etc. I.e. a form of embedding/dimension reduction (with the caveat the goal may not be a lower dimensional representation but one of equal dimensionality, but more meaningfully expressed):


  Feature embedding is an emerging research area which intends to transform features from the original space into a new space to support effective learning. 



Generalized Feature Embedding for Supervised, Unsupervised, and Online Learning Tasks (2019)



  Feature embedding aims to learn a low-dimensional vector
  representation for each instance to preserve the information
  in its features.



Large-Scale Heterogeneous Feature Embedding (2019)